We consider the deconvolution problem of estimating an image from a noisy blurred version of it. In particular, we are interested in the boundary effects: since the convolution operator is non-local, the blurred image...
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We consider the deconvolution problem of estimating an image from a noisy blurred version of it. In particular, we are interested in the boundary effects: since the convolution operator is non-local, the blurred image depend on the scenery outside the field of view. Ignoring this dependency leads to image distortion known as boundary effect. In this article, we consider two different approaches to treat the non-locality. One is to estimate the image extended outside the field of view. The other is to treat the influence of the out of view scenery as boundary clutter. Both approaches are considered from the Bayesian point of view.
We look into the optimal structure for the DTV (Digital TV) receiver system with an array antenna. In this paper, we apply the ML(Maximum likelihood) approach, which is a classical method in the theory of detection an...
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We look into the optimal structure for the DTV (Digital TV) receiver system with an array antenna. In this paper, we apply the ML(Maximum likelihood) approach, which is a classical method in the theory of detection and estimation. And we examine the limitation of it. It is that the number of multi-paths should be less than that of antennas. But it conflicts with the indoor channel environment. To deal with this problem, we propose a sub-optimal structure, which has lower complexity and computation load, as compared with the optimal structure. And to verify the performance, we compare the SER(symbol error rate) curve of each system by computer simulation.
Wireless sensor networks (WSNs) have attracted considerable attention in recent years and motivate a host of new challenges for distributed signalprocessing. The problem of distributed or decentralized estimation has...
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Wireless sensor networks (WSNs) have attracted considerable attention in recent years and motivate a host of new challenges for distributed signalprocessing. The problem of distributed or decentralized estimation has often been considered in the context of parametric models. However, the success of parametric methods is limited by the appropriateness of the strong statistical assumptions made by the models. In this paper, a more flexible nonparametric model for distributed regression is considered that is applicable in a variety of WSN applications including field estimation. Here, starting with the standard regularized kernel least-squares estimator, a message-passing algorithm for distributed estimation in WSNs is derived. The algorithm can be viewed as an instantiation of the successive orthogonal projection (SOP) algorithm. Various practical aspects of the algorithm are discussed and several numerical simulations validate the potential of the approach.
The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal correlation structure or limited proces...
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The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal correlation structure or limited processing capability it;is reasonable to use the simple quadratic detector that is optimal in the case of an independent and identically distributed (i.i.d.) signal. Using the large deviations principle, the performance of this detector (which is suboptimal for non-i.i.d. signals) is compared with that of the optimal detector for correlated signals via the asymptotic relative efficiency defined as the ratio between sample sizes of two detectors required for the same performance in the large-sample-size regime. The effects of SNR on the ARE are investigated. It is shown that the asymptotic efficiency of the simple quadratic detector relative to the optimal detector converges to one as the SNR increases without bound for any bounded spectrum, and that the simple quadratic detector performs as well as the optimal detector for a wide range of the correlation values at high SNR.
We propose an output signal selection method for the directional diversity in VSB receiver which is to improve the reception performance of VSB system in severe Rayleigh fading channel. The VSB system has only about 0...
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We propose an output signal selection method for the directional diversity in VSB receiver which is to improve the reception performance of VSB system in severe Rayleigh fading channel. The VSB system has only about 0.3% of known training signal for the receiver in a data field and the reception performance of VSB receiver is degraded significantly when there are near-0 dB ghosts in received signal. To overcome this problem, the directional diversity is suggested. In directional diversity the selection of an output signal with best channel condition in point of VSB equalizer is very important to improve VSB reception performance. For the selection of the optimal signal, we extracted channel profiles in time domain for all the signals by correlating the PN511 sequence in VSB field sync and selected one signal by comparing the channel profiles. The simulation results show that the proposed method selects a signal with the best channel condition among the signals, so the reception performance of the VSB system can be improved in severe Rayleigh channels.
When the short-time Fourier transform (STFT) of an audio signal is arbitrarily modified, it no longer truly represents a time-domain signal. Classically, the accepted solution to obtain a time-domain signal from a mod...
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When the short-time Fourier transform (STFT) of an audio signal is arbitrarily modified, it no longer truly represents a time-domain signal. Classically, the accepted solution to obtain a time-domain signal from a modified STFT (MSTFT) is to invert the MSTFT to a time-domain signal that has an STFT that is closest to the MSTFT in a least squares sense. This is also the approach currently taken by our modulation filtering techniques. However, it was never established that using the original and unmodified STFT phase in this reconstruction is optimal for modulation filtering. In this paper, we compare our signal reconstruction approach to a well-known iterative procedure that approximates a time-domain signal using only the STFT magnitude. We analyze the signal reconstruction of speech signals after filtering them with low-pass, band-pass and high-pass modulation filters. Our study shows that the iterative procedure yields quantitatively and qualitatively comparable signals at significantly higher computational cost. It therefore does not seem a worthwhile alternative to our current reconstruction technique, but it may prove useful for IIR modulation filtering.
For an assessment of the power quality in power distribution systems, classical Fourier series-based power quality indices are normally employed. The classical Fourier series-based power quality indices assume the per...
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For an assessment of the power quality in power distribution systems, classical Fourier series-based power quality indices are normally employed. The classical Fourier series-based power quality indices assume the periodicity of the disturbance so that the applications are limited to the harmonics. Hence, it is necessary for us to redefine power quality indices for the "transient" disturbances. In this paper, development of time-frequency based power quality indices are discussed for an assessment of transient power quality. The time and frequency localized information of the transient disturbance signals will be utilized for a new definition of the transient power quality indices. As an example of time-frequency based power quality indices, new definition of transient telephone interference factor has been carefully derived and verified in comparison with traditional telephone interference factor has been carefully derived and verified in comparison with traditional telephone interference factor. Time-frequency based power quality indices allow one to quantify the effects of transient disturbances by time and frequency localized information.
Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analy...
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Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations.1,2 Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method3 to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.
Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through ...
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Wireless sensor networks present a number of challenges to system designers, including notably the efficient use of limited resources such as bandwidth and energy. One way these challenges can be addressed is through the application of signalprocessing principles in the design, deployment and operation of sensor networks. After a discussion of general issues arising in this context, this talk will describe several recent developments in this area. These include the effects of receiver choice on energy efficiency, collaborative beam-forming, sensor scheduling, and distributed learning. Some of the work described in this talk can be found in Refs. 1-8.
Distributed sensor networks have been proposed for a wide range of applications. In this paper, our goal is to locate a wideband source, generating both acoustic and seismic signals, using both seismic and acoustic se...
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Distributed sensor networks have been proposed for a wide range of applications. In this paper, our goal is to locate a wideband source, generating both acoustic and seismic signals, using both seismic and acoustic sensors. For a far-field acoustic source, only the direction-of-arrival (DOA) in the coordinate system of the sensors is observable. We use the approximate Maximum-Likelihood (AML) method for DOA estimations from several acoustic arrays. For a seismic source, we use data collected at a single tri-axial accelerometer to perform DOA estimation. Two seismic DOA estimation methods, the eigen-decomposition of the sample covariance matrix method and the surface wave method are used. Field measurements of acoustic and seismic signals generated by vertically striking a heavy metal plate placed on the ground in an open field are collected. Each acoustic array uses four low-cost microphones placed in a square configuration and separated by one meter. The microphone outputs of each array are collected by a synchronized A/D recording system and processed locally based on the AML algorithm for DOA estimation. An array of six tri-axial accelerometers arranged in two rows whose outputs are fed into an ultra low power and high resolution network-aware seismic recording system. Field measured data from the acoustic and seismic arrays show the estimated DOAs and consequent localizations of the source are quite accurate and useful. Beamforming, Source localization,.
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